Tag
Data structures
3 diagram-led guides on Data structures by Abhishek Goyal.
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Deep diveNewMembers
Data Structures for System Design: B-Tree, LSM Tree, Bloom Filter, Inverted Index, Geo and Vector Indexes
The data structures behind real databases and search engines, explained for system design interviews: B-Tree vs LSM tree, Bloom filters, tries and FSTs for autocomplete, the inverted index, Roaring bitmaps, geohash, quadtree, S2 and H3 for location search, and HNSW for vector search, with when to pick each.
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How Search Engines Work: Inverted Index, Text Analysis, TF-IDF and BM25
How a full-text search engine finds and ranks results: the inverted index, text analysis (tokenising, stemming, stop words), postings lists and boolean queries, TF-IDF and BM25 scoring, Lucene segments and merges, and near-real-time refresh, explained from the book-index analogy up to system design interview answers.
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Deep diveNewMembers
How Google Search Works: Crawling, Indexing, Ranking and Serving at Scale
How Google Search works, explained for system design interviews: a polite web crawler with a URL frontier and robots.txt, the inverted index, PageRank with the random surfer, why Google shards its index by document, serving with caches and index servers, and the move from batch rebuilds to Caffeine and Percolator.
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